Project Setup (Logger ,Exception ,setup file)
In this session, we dive into the crucial aspects of setting up a robust project environment, including logging, exception handling, and creating a setup file. These elements are essential for maintaining, debugging, and deploying your machine learning projects effectively.
🔍 In this session, we will cover:
Introduction to Project Setup: Understanding the importance of a well-structured project environment.
Setting Up Logging:
What is Logging?: Importance of logging in monitoring and debugging applications.
Python Logging Module: Overview of the logging module in Python.
Basic Logging Setup: Configuring a basic logging setup.
Logging Levels: Understanding different logging levels (DEBUG, INFO, WARNING, ERROR, CRITICAL).
Logging to Files: Configuring logging to output to files for persistent logs.
Advanced Logging Configuration: Customizing log formats, handlers, and loggers.
Exception Handling:
Understanding Exceptions: Types of exceptions and their significance in robust code.
Try-Except Blocks: Using try-except blocks for handling exceptions.
Custom Exception Classes: Creating custom exception classes for specific error handling.
Logging Exceptions: Integrating logging with exception handling to capture errors effectively.
Best Practices: Tips for effective exception handling and logging in machine learning projects.
-Creating a Setup File:
Introduction to Setup Files: Purpose and benefits of having a setup file in your project.
Writing a setup.py File: Step-by-step guide to creating a setup.py file.
Defining Project Metadata: Specifying project name, version, author, and description.
Listing Dependencies: Specifying required packages and dependencies.
-Including Package Data: Ensuring all necessary data files are included in the package.
Building and Distributing: Building your package and distributing it using tools like setuptools and pip.
-Organizing Your Project: Best practices for structuring your project directory.
Module and Package Organization: How to organize your code into modules and packages.
Configuration Files: Managing configuration settings with config files.
Hands-On Examples: Practical demonstrations of setting up logging, exception handling, and creating a setup file in a machine learning project.
Q&A and Troubleshooting: Addressing common questions and providing tips for effectively setting up your project environment.
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